Resiliency in exascale systems and computations using chaotic-identity maps

Nageswara S.V. Rao

doi:10.1007/978-3-642-36949-0_55

Resiliency in exascale systems and computations using chaotic-identity maps

Nageswara S.V. Rao

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

For exascale computing systems, we propose (i) light-weight computational modules that utilize chaotic computations and customized identity maps to detect component failures, and (ii) statistical estimation methods that generate robustness estimates for the system and computations based on the module outputs. The diagnosis modules execute multiple Poincare and identity maps, which are customized to detect certain classes of failures in the compute nodes and interconnects. We propose statistical methods that generate robustness estimates for the system using the outputs of pipelined chains of diagnosis modules.

Original language	English
Title of host publication	Euro-Par 2012 - Parallel Processing Workshops
Subtitle of host publication	BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Revised Selected Papers
Pages	494-495
Number of pages	2
DOIs	https://doi.org/10.1007/978-3-642-36949-0_55
State	Published - 2013
Event	Parallel Processing Workshops, Euro-Par 2012: BDMC 2012, CGWS 2012, HeteroPar 2012, HiBB 2012, OMHI 2012, Paraphrase 2012, PROPER 2012, Resilience 2012, UCHPC 2012, VHPC 2012 - Rhodes Island, Greece Duration: Aug 27 2012 → Aug 31 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7640 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Parallel Processing Workshops, Euro-Par 2012: BDMC 2012, CGWS 2012, HeteroPar 2012, HiBB 2012, OMHI 2012, Paraphrase 2012, PROPER 2012, Resilience 2012, UCHPC 2012, VHPC 2012
Country/Territory	Greece
City	Rhodes Island
Period	08/27/12 → 08/31/12

Keywords

Exascale systems
chaotic maps
resiliency
statistical estimation

Access to Document

10.1007/978-3-642-36949-0_55

Cite this

Rao, N. S. V. (2013). Resiliency in exascale systems and computations using chaotic-identity maps. In Euro-Par 2012 - Parallel Processing Workshops: BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Revised Selected Papers (pp. 494-495). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7640 LNCS). https://doi.org/10.1007/978-3-642-36949-0_55

Rao, Nageswara S.V. / Resiliency in exascale systems and computations using chaotic-identity maps. Euro-Par 2012 - Parallel Processing Workshops: BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Revised Selected Papers. 2013. pp. 494-495 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Resiliency in exascale systems and computations using chaotic-identity maps",

abstract = "For exascale computing systems, we propose (i) light-weight computational modules that utilize chaotic computations and customized identity maps to detect component failures, and (ii) statistical estimation methods that generate robustness estimates for the system and computations based on the module outputs. The diagnosis modules execute multiple Poincare and identity maps, which are customized to detect certain classes of failures in the compute nodes and interconnects. We propose statistical methods that generate robustness estimates for the system using the outputs of pipelined chains of diagnosis modules.",

keywords = "Exascale systems, chaotic maps, resiliency, statistical estimation",

author = "Rao, \{Nageswara S.V.\}",

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doi = "10.1007/978-3-642-36949-0\_55",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "494--495",

booktitle = "Euro-Par 2012 - Parallel Processing Workshops",

note = "Parallel Processing Workshops, Euro-Par 2012: BDMC 2012, CGWS 2012, HeteroPar 2012, HiBB 2012, OMHI 2012, Paraphrase 2012, PROPER 2012, Resilience 2012, UCHPC 2012, VHPC 2012 ; Conference date: 27-08-2012 Through 31-08-2012",

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Rao, NSV 2013, Resiliency in exascale systems and computations using chaotic-identity maps. in Euro-Par 2012 - Parallel Processing Workshops: BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7640 LNCS, pp. 494-495, Parallel Processing Workshops, Euro-Par 2012: BDMC 2012, CGWS 2012, HeteroPar 2012, HiBB 2012, OMHI 2012, Paraphrase 2012, PROPER 2012, Resilience 2012, UCHPC 2012, VHPC 2012, Rhodes Island, Greece, 08/27/12. https://doi.org/10.1007/978-3-642-36949-0_55

Resiliency in exascale systems and computations using chaotic-identity maps. / Rao, Nageswara S.V.
Euro-Par 2012 - Parallel Processing Workshops: BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Revised Selected Papers. 2013. p. 494-495 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7640 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Rao, Nageswara S.V.

PY - 2013

Y1 - 2013

N2 - For exascale computing systems, we propose (i) light-weight computational modules that utilize chaotic computations and customized identity maps to detect component failures, and (ii) statistical estimation methods that generate robustness estimates for the system and computations based on the module outputs. The diagnosis modules execute multiple Poincare and identity maps, which are customized to detect certain classes of failures in the compute nodes and interconnects. We propose statistical methods that generate robustness estimates for the system using the outputs of pipelined chains of diagnosis modules.

AB - For exascale computing systems, we propose (i) light-weight computational modules that utilize chaotic computations and customized identity maps to detect component failures, and (ii) statistical estimation methods that generate robustness estimates for the system and computations based on the module outputs. The diagnosis modules execute multiple Poincare and identity maps, which are customized to detect certain classes of failures in the compute nodes and interconnects. We propose statistical methods that generate robustness estimates for the system using the outputs of pipelined chains of diagnosis modules.

KW - Exascale systems

KW - chaotic maps

KW - resiliency

KW - statistical estimation

UR - https://www.scopus.com/pages/publications/84874408654

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DO - 10.1007/978-3-642-36949-0_55

M3 - Conference contribution

AN - SCOPUS:84874408654

SN - 9783642369483

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Euro-Par 2012 - Parallel Processing Workshops

T2 - Parallel Processing Workshops, Euro-Par 2012: BDMC 2012, CGWS 2012, HeteroPar 2012, HiBB 2012, OMHI 2012, Paraphrase 2012, PROPER 2012, Resilience 2012, UCHPC 2012, VHPC 2012

Y2 - 27 August 2012 through 31 August 2012

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Rao NSV. Resiliency in exascale systems and computations using chaotic-identity maps. In Euro-Par 2012 - Parallel Processing Workshops: BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Revised Selected Papers. 2013. p. 494-495. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-36949-0_55

Resiliency in exascale systems and computations using chaotic-identity maps

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